Assist. Prof. Dr. Hye-Youn Lim | Computer Vision | Excellence in Research Award

Posted on by Global Sensor Awards

Assist. Prof. Dr. Hye-Youn Lim | Computer Vision | Excellence in Research Award

Assist. Prof. Dr. Hye-Youn Lim | Computer Vision | Dong-A University | South Korea

Assist. Prof. Dr Hye-Youn Lim is a distinguished researcher and academic in artificial intelligence, computer vision, and intelligent systems, serving in the Department of Electronics Engineering at Dong-A University, Republic of Korea. Hye-Youn Lim obtained her Ph.D. from a leading research university and has accumulated extensive professional experience, including leading national and international research projects and collaborating with multiple industry partners on AI-based technology applications. Her research interests focus on intelligent video analysis, visual recognition, and smart city applications, demonstrating her expertise in applying computational methods to real-world problems. Hye-Youn Lim possesses a diverse set of research skills, including deep learning model development, attention-driven network design, data preprocessing and augmentation strategies, and applied computer vision for automated systems. Her scholarly output includes more than 30 SCI- and Scopus-indexed journal articles, with verified metrics of 22 Scopus documents, over 100 citations, and a recorded h-index, reflecting both impact and consistency in high-quality research dissemination.

Citation Metrics (Scopus)

120

90

60

30

0

Citations
105

Documents
22

h-index
3

Citations
Documents
h-index

View Scopus Profile
 View ORCID Profile

Featured Publications

Mr. Suresha R | Computer Vision Awards | Excellence in Research Award

Posted on by Global Sensor Awards

Mr. Suresha R | Computer Vision Awards | Excellence in Research Award 

Mr. Suresha R | Computer Vision Awards | Amrita Vishwa Vidyapeetham | India

Mr. Suresha R. is a results-driven educator and technologist with over six years of combined experience in teaching computer science and academic leadership. He holds an M.Sc. in Computer Science and has qualified in UGC-NET and K-SET, while currently pursuing a Ph.D. Mr. Suresha R. has demonstrated expertise in curriculum design and research, particularly focusing on AI in autonomous solutions and computer vision applications. In his professional career, Mr. Suresha R. has served as an Assistant Professor at Amrita Vishwa Vidyapeetham, School of Computing, Mysuru Campus, and at SBRR Mahajana First Grade College, Mysuru, where he delivered advanced courses in Computer Vision, Digital Image Processing, Pattern Recognition, Computational Intelligence, Computer Graphics, Machine Learning, Exploratory Data Analysis, R Programming, Information Retrieval, Data Mining, Numerical Analysis, and Operations Research, consistently achieving high student satisfaction. His research interests encompass small traffic sign detection and recognition in challenging scenarios using computer vision and LiDAR-based techniques with ROS2 framework, deep learning-based vehicle detection and distance estimation for autonomous systems, motion blur image restoration, wild animal recognition through vocal analysis, and SVM-based medical image classification. Mr. Suresha . possesses strong research skills in Python, MATLAB, ROS2, machine learning, deep learning, image processing, and data analysis. He has successfully guided Bachelor’s and Master’s students in research projects, fostering innovation and academic growth. His academic contributions are recognized through multiple publications in prestigious journals and conferences, including IEEE Access, Procedia Computer Science, ICCCNT, CCEM, ICECAA, and INDIACom. Mr. Suresha . has a proven record of collaborating in interdisciplinary teams, effectively communicating complex technical concepts, and mentoring students to achieve excellence in research and practical applications. His dedication to lifelong learning and active engagement in both teaching and research demonstrates his commitment to advancing knowledge in computer science and autonomous systems. Throughout his career, Suresha  has received awards and recognitions for research excellence, contributing to the development of sustainable and intelligent solutions in the field of computer vision and AI. Overall, Mr. Suresha exemplifies a passionate and innovative professional, bridging theoretical foundations with applied research, and continues to make significant contributions to academia and technology

Professional Profiles: ORCID

Selected Publications 

  1. Suresha, R., Manohar, N., Ajay Kumar, G., & Singh, R. (2024). Recent advancement in small traffic sign detection: Approaches and dataset.

  2. Suresha, R., Manohar, N., & Jipeng, T. (2024). Two-stage traffic sign classification system.

  3. Sudharshan Duth, P., Manohar, N., Suresha, R., Priyanka, M., & Jipeng, T. (2024). Wild animal recognition: A vocal analysis.

  4. Suresha, R., Jayanth, R., & Shriharikoushik, M. A. (2023). Computer vision approach for motion blur image restoration system.

  5. Srinivasa, C., Suresha, R., Manohar, N., Dharun, G. K., Sheela, T., & Jipeng, T. (2023). Deep learning-based techniques for precise vehicle detection and distance estimation in autonomous systems.

  6. Suresha, R., Devika, K. M., & Prabhu, A. (2022). Support vector machine classifier based lung cancer recognition: A fusion approach.

Ms. Leiyao Liao | Deep Learning Awards | Best Researcher Award

Posted on by Global Sensor Awards

Ms. Leiyao Liao | Deep Learning Awards | Best Researcher Award

Ms. Leiyao Liao | Deep Learning Awards | Nanjing University Of Posts And Telecommunications | China

Ms. Leiyao Liao is a distinguished researcher and lecturer at the School of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, renowned for her contributions to synthetic aperture radar (SAR) image understanding, target recognition, and explainable deep learning. She obtained her Doctorate in Electronic Science and Technology from Xi’an University of Electronic Science and Technology, where she developed a solid foundation in radar signal processing and mechanism-driven neural networks, and her Bachelor of Science from the same institution, focusing on communication and information systems. In her professional career, Ms. Liao has demonstrated exceptional leadership and technical expertise through her involvement in multiple national-level research projects, including those funded by the National Natural Science Foundation of China and the Central Military Commission, where she played key roles in advancing interpretable deep models for radar target analysis. Her primary research interests encompass synthetic aperture radar (SAR) target recognition, explainable deep learning, mechanism-driven neural networks, radar signal processing, and multimodal intelligent sensing, with a particular focus on small object detection and imbalanced recognition in complex environments. Ms. Liao’s research skills include advanced radar data analysis, model interpretability design, and deep probabilistic modeling, complemented by proficiency in simulation, signal processing, and algorithmic optimization. Her impactful body of work includes 16 Scopus-indexed publications, accumulating 187 citations with an h-index of 7, highlighting her growing international recognition. She has published extensively in high-impact journals such as IEEE Transactions on Geoscience and Remote Sensing (TGRS), IEEE Geoscience and Remote Sensing Letters (GRSL), IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), and IEEE Journal of Selected Topics in Signal Processing (JSTSP). Ms. Liao has received multiple academic honors and research commendations for her outstanding contributions to radar intelligence and interpretability, reflecting her dedication to bridging the gap between physical modeling and deep learning.

Professional Profiles: Scopus

Featured Publications 

  1. Liao, L. (2025). Integrated Physically Interpretable Model for SAR Target Recognition. IEEE Geoscience and Remote Sensing Letters. (Citations: 26)

  2. Liao, L. (2025). Research on Collision Access Method for Satellite Internet of Things Based on Bayliss Window Function. Sensors (Basel, Switzerland). (Citations: 0)

  3. Liao, L. (2024). EMI-Net: Interpretable Deep Network for SAR Target Recognition. IEEE Transactions on Geoscience and Remote Sensing. (Citations: 41)

  4. Liao, L. (2024). Based on Physical Solvability: Mechanism-Driven Neural Networks for Radar Target Understanding. Journal of Electronics. (Citations: 18)

  5. Liao, L. (2022). Interpretable Deep Probabilistic Model for HRR Radar Signal and Its Application to Target Recognition. IEEE Journal of Selected Topics in Signal Processing. (Citations: 52)

  6. Liao, L. (2023). Fusion-Based Multimodal SAR Target Classification Using Explainable Deep Learning. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. (Citations: 29)

  7. Liao, L. (2023). Mechanism-Driven Deep Learning for Small Object Detection in Complex Radar Scenarios. IEEE Access. (Citations: 21)

Prof. Din-Yuen Chan | Deep Learning | Best Scholar Award

Posted on by Global Sensor Awards

Prof. Din-Yuen Chan | Deep Learning | Best Scholar Award 

Prof. Din-Yuen Chan, National Chiayi University, Taiwan

Din-Yuen Chan is a prominent scholar in electrical engineering with extensive experience in visual signal processing and computer vision. He earned his Ph.D. in Electrical Engineering from National Cheng Kung University, Taiwan, in 1996. A member of the Visual Signal Processing and Communication Technical Committee (VSPC TC) since 2010, he served as the founding director of the Department of Electrical Engineering (2007–2011) and as Dean of the College of Science and Engineering at National Chiayi University (2017–2020). His research spans semantic object detection, video/audio coding, stereoscopic 3D, AI-based pattern recognition, and deep learning neural networks. In the past five years, he has published multiple SCI-indexed journal papers on topics such as stereo matching, instance segmentation, speaker diarization, depth estimation, and autonomous robotics. As a frequent corresponding author, he continues to lead innovations in applied AI and multimedia processing.

Professional Profile:

SCOPUS

Summary of Suitability for the Best Scholar Award

Dr. Din-Yuen Chan has maintained an outstanding academic career for over two decades, contributing significantly to the fields of electrical engineering and computer vision. His long-standing commitment to advancing knowledge is reflected in his leadership roles and consistent research output in areas such as semantic object detection, AI-based pattern recognition, video/audio coding, and stereoscopic 3D.

🎓 Education

  • Ph.D. in Electrical Engineering
    National Cheng Kung University, Taiwan 🇹🇼
    Completed in 1996

💼 Work Experience

  • 🧠 Member, Visual Signal Processing and Communication Technical Committee (VSPC TC)
    Since 2010

  • 🏛️ Founding Director, Department of Electrical Engineering, National Chiayi University
    2007 – 2011

  • 🎓 Dean, College of Science and Engineering, National Chiayi University
    2017 – 2020

🧪 Research Interests

  • 🔍 Computer Vision

  • 🎯 Semantic Object Detection

  • 🎞️ Video/Audio Coding

  • 🤖 AI-based Pattern Recognition

  • 🥽 Stereoscopic 3D

  • 🧠 Deep Learning Neural Networks

🏅 Achievements & Honors

  • ✍️ Published multiple SCI-indexed journal papers in high-impact venues, including:

    • EURASIP Journal on Image and Video Processing

    • IET Computer Vision

    • Multimedia Tools and Applications

    • Applied Sciences

  • ⭐ First or corresponding author in many significant papers on stereo matching, depth estimation, 3D object placement, and speaker diarization.

  • 🤖 Developed a low-cost autonomous outdoor robot with end-to-end deep learning navigation.

  • 🧏 Invented a new speaker-diarization technology using spectral-LSTM.

  • 🎓 Recognized leader in academia for establishing and leading research and administrative departments.

Publication Top Notes:

A new speaker-diarization technology with denoising spectral-LSTM for online automatic multi-dialogue recording

Natural-Prosodic Cross-Lingual Personalized TTS

New Efficient Depth Estimation and Real-Time Object 3D Recognition Models for Humanoid Robotic Environment Understanding

Rational 3D object placement based on deep learning based plane detection

INTEGRATED LIGHT-RESNET AND POOLFORMER NETWORKS FOR SHAPE-PRESERVING LANE DETECTION

Mr. Mohammed Aljamal | Artificial Intelligence | Best Researcher Award

Posted on by Global Sensor Awards

Mr. Mohammed Aljamal | Artificial Intelligence | Best Researcher Award 

Mr. Mohammed Aljamal, University of Bridgeport, United States

Mohammed Aljamal is a Laboratory Engineer and Ph.D. candidate in Computer Science & Engineering, based in the New York City Metropolitan Area. He holds a Master’s degree in Artificial Intelligence from the University of Bridgeport and is actively engaged in academic and professional communities as the President of the UB Robotics Club and a member of AIAA, UPE, and the Honor Society. With over four years of experience at the University of Bridgeport, he has contributed as a Laboratory Engineer, Graduate Research Assistant, and Teaching Assistant, specializing in laboratory management, hardware and software solutions, and IT infrastructure. His expertise spans project leadership, problem-solving, cross-functional team management, and innovative solution design. Beyond academia, Mohammed has a strong background in consulting, resource allocation, and international collaboration, having successfully led and completed critical projects. Passionate about technology and innovation, he continuously seeks opportunities to develop solutions that enhance user experiences and drive technological advancement.

Professional Profile:

GOOGLE SCHOLAR

Suitability of Mohammed Aljamal for the Best Researcher Award

Mohammed Aljamal is a highly skilled and innovative researcher with a strong background in Artificial Intelligence, Computer Science, and Engineering. His Ph.D. candidacy, extensive teaching experience, and leadership roles at the University of Bridgeport demonstrate his dedication to academic excellence and technological advancements.

Education 🎓

  • Ph.D. Candidate in Computer Science & Engineering – University of Bridgeport (Ongoing)
  • Master’s Degree in Artificial Intelligence – University of Bridgeport
  • Bachelor’s Degree in [Field Not Specified] – [University Not Specified]

Work Experience 💼

University of Bridgeport (4 years 1 month)

  • Labs Engineer (Feb 2022 – Present) ⚙️

    • Improved and maintained laboratory equipment.
    • Developed detailed hardware and software data for lab management.
    • Conducted inspections and routine maintenance on lab equipment.
    • Implemented new technology solutions and disaster recovery plans.
    • Coordinated IT services to ensure data availability and security.

  • Graduate Research & Teaching Assistant (Jan 2022 – Feb 2022) 📚

    • Assisted in research projects and student instruction.

  • Teaching and Laboratory Assistant (Feb 2021 – Dec 2021) 🏫

    • Assisted undergraduate and graduate students in Intro to Robotics.
    • Managed lab hours, discussions, assignments, and exams.

Achievements & Leadership 🌟

  • President of UB Robotics Club 🤖 – Leading robotics initiatives and student projects.
  • Successfully completed two delayed projects 🎯 – Resolved critical issues and met client satisfaction.
  • Consulted and collaborated with international vendors 🌍 – Gained experience in global tech solutions.
  • Designed and implemented innovative lab solutions 🔧 – Optimized university lab resources.

Awards & Honors 🏆

  • Member of AIAA (American Institute of Aeronautics and Astronautics) 🚀
  • Member of UPE (Upsilon Pi Epsilon – International Honor Society for Computing) 🖥️
  • Honor Society Member 🎖️

Publication Top Notes:

 

 

Dr. Jany Shabu | Artificial Intelligence Awards | Best Researcher Award

Posted on by Global Sensor Awards

Dr. Jany Shabu | Artificial Intelligence Awards | Best Researcher Award 

Dr. Jany Shabu, Sathyabama Institute of Science & Technology, India

Dr. S.L. Jany Shabu is an accomplished Associate Professor in the Department of Computer Science Engineering at Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India. With a Ph.D. in Image Fusion, her research focuses on multimodal image fusion using intelligent optimization techniques, particularly in the context of brain tumor detection. Dr. Shabu has a strong academic background, holding both M.Tech and MS degrees in Information Technology, and has published extensively, with 58 papers indexed in Scopus and four in WoS. She has received multiple accolades for her contributions to research and education, including cash awards for publishing in high-impact journals and the prestigious NPTEL Discipline Star Certificate. As an active member of the National Institute for Technical Training and Skill Development, Dr. Shabu is dedicated to advancing the field of computer science through her research, teaching, and professional engagement. Her innovative projects, including a Safety Stick for Elders, and her patents in smart traffic control and gesture-based systems, exemplify her commitment to leveraging technology for societal benefit. She has also authored several books on machine learning, cloud computing, and data analytics, further solidifying her reputation as a thought leader in her field. With a robust online presence, including profiles on ORCID and Scopus, Dr. Shabu continues to contribute to academic excellence and innovation in computer science.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award:

Dr. S.L. Jany Shabu is a commendable candidate for the Best Researcher Award, recognized for her significant contributions to computer science engineering and her innovative research in image fusion and optimization techniques.

Education 🎓

  • Ph.D. in Image Fusion
    Sathyabama Institute of Science and Technology
    Thesis Title: Multimodal Image Fusion using Intelligent Optimization Techniques with Brain Tumor Detection
  • M.Tech (IT) in Information Technology
    Sathyabama Institute of Science and Technology
    Graduated with First Class
  • M.S. (IT) in Information Technology
    Manonmaniam Sundaranar University
    Graduated with First Class

Work Experience 💼

  • Current Position: Associate Professor, Computer Science Engineering
    Sathyabama Institute of Science and Technology

Achievements 🌟

  • Seed Funding:
    Project Title: Safety Stick for Elders
    Amount: ₹300,000
    Period: Oct 2021 – June 2022
    Role: Co Principal Investigator
  • Patent Holder:
    1. SMART TRAFFIC CONTROL SYSTEM USING IOT BASED MONITORING SYSTEM
      Application No: 201741038384 – Published
    2. GARMENT STEAMER MANAGEMENT SYSTEM
      Application No: 367890-001 – Published
    3. GESTURE BASED ELECTRONIC GADGET OPERATING SYSTEM
      Application No: 202341088351 A – Published
  • Reviewer:
    • Journal of Scientific Research and Reports
    • Journal of Pharmaceutical Research International
    • International Conference on Computational Intelligence, Networks & Security
    • Book Chapter for CRC PRESS Taylor & Francis Group

Awards and Honors 🏆

  • Cash Award for Publishing Paper in High Impact WOS Journal
    Sathyabama Institute of Science and Technology (Teachers Day 2022 & 2024)
  • NPTEL Discipline Star Certificate
  • Disciplinarian Award
    Sathyabama Institute of Science & Technology, Chennai

Publication Top Notes:

DeepExuDetectNet: Diabetic retinopathy diagnosis: Blood vessel segmentation and exudates disease detection in fundus images

A swarm intelligence optimization for lung cancer detection from RNA-seq gene expression data using convolutional neural networks

A novel framework for entertainment robots in personalized elderly care using adaptive emotional resonance technologies

An Improved Adaptive Neuro-fuzzy Inference Framework for Lung Cancer Detection and Prediction on Internet of Medical Things Platform

Rainfall prediction using machine learning techniques

Online product review using sentiment analysis

Mr. Shiraz Kaderuppan | Deep Learning Awards | Best Researcher Award

Posted on by Global Sensor Awards

Mr. Shiraz Kaderuppan | Deep Learning Awards | Best Researcher Award 

Mr. Shiraz Kaderuppan, Newcastle University, Singapore

Shiraz is a Singaporean educator and data analytics enthusiast with extensive experience in enhancing deep neural network (DNN) architectures for feature recognition and extraction in image processing applications. With a solid background in software development and embedded systems programming, he has successfully developed desktop applications that integrate advanced image processing algorithms. Currently serving as an Associate Lecturer at Republic Polytechnic, Shiraz teaches courses in Financial Technology, Business Intelligence, and Distributed Ledger Technology while conducting professional training programs for various organizations in Microsoft Office applications. He is also an accomplished application developer, utilizing machine learning and artificial intelligence for predictive analytics and data analysis. His passion for empowering others extends to teaching Mathematics and Science at secondary and junior college levels, demonstrating his commitment to education and skill development in the IT field.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award: 

Shiraz S/O Kaderuppan stands out as a highly suitable candidate for the Best Researcher Award due to his extensive experience and impressive contributions to the field of data analytics and deep learning, particularly in image processing applications. His career reflects a strong commitment to advancing technology through research and education.

Education 🎓

  • Republic Polytechnic
    Diploma in Financial Technology, Business Intelligence & Distributed Ledger Technology
    Mar 2023 – Present

Work Experience 💼

  • Associate Lecturer
    Republic Polytechnic
    Mar 2023 – Present

    • Conducted courses for diploma students in Financial Technology, Business Intelligence, and DLT solutioning.
  • Corporate Trainer
    Self-Employed
    Jul 2014 – Present

    • Provided training for corporate clients and private individuals in advanced Microsoft Office applications and IBM products.
  • Application Developer
    Self-Employed
    May 2012 – Present

    • Developed desktop applications using C# .NET, interfacing with microcontrollers and implementing machine learning algorithms.
  • ML/AI Developer
    Self-Employed
    Sep 2008 – Present

    • Applied machine learning and deep learning algorithms for data analysis and forecasting.
  • Educator
    Self-Employed
    Aug 2010 – Present

    • Provided secondary school and JC-level tuition for Mathematics and Science subjects.
  • General Education Officer (Teacher)
    Ministry of Education
    Sep 2007 – Jan 2009

    • Taught Biology, Chemistry, and General Science at Tampines and Bedok North Secondary Schools.
  • Founder & Business Development Manager
    Self-Employed
    Jan 2005 – Jun 2007

    • Managed retail of scientific components globally and established a network of professional purchasers.

Achievements 🌟

  • Successfully conducted numerous training programs for companies and government bodies, focusing on advanced features of Microsoft Office for business intelligence and data analysis.
  • Developed and implemented desktop applications that effectively integrate hardware devices with advanced image processing algorithms.
  • Empowered project managers to utilize Microsoft Project for effective project planning and resource management.

Awards & Honors 🏆

  • Recognized for excellence in teaching and training methodologies at Republic Polytechnic and in corporate training programs.
  • Selected as a participant in the SkillsFuture for Digital Workplace Initiative for promoting digital literacy and skills enhancement in Singapore.

Publication Top Notes:

Θ-Net: A Deep Neural Network Architecture for the Resolution Enhancement of Phase-Modulated Optical Micrographs In Silico

O-Net: A Fast and Precise Deep-Learning Architecture for Computational Super-Resolved Phase-Modulated Optical Microscopy

Smart Nanoscopy: A Review of Computational Approaches to Achieve Super-Resolved Optical Microscopy

Kanika | Machine Learning | Best Researcher Award

Posted on by Global Sensor Awards

Kanika | Machine Learning | Best Researcher Award

Ms. Kanika, National institute of technology Agartala, India.

Ms. Kanika, hailing from Hasanpur, Haryana, is an enthusiastic researcher with a strong passion for applied mathematics 🧮 and advanced computing technologies 💻. Her expertise spans optimization, uncertainty theory, numerical analysis, graph theory, artificial intelligence 🤖, and machine learning. With an M.Sc. in Mathematics and Computing 🎓 from NIT Agartala, where she ranked 6th, and a B.Sc. in Mathematics, Physics, and Computer Science 🎓 from Banasthali Vidyapith, she has consistently demonstrated academic excellence. Kanika is driven to solve real-life problems 🌍 through mathematics and is currently working on a machine-learning research paper while aspiring to contribute to computational imaging and AI.

Publication Profiles 

Googlescholar

Education and Experience

Education 🎓
  • M.Sc. in Mathematics and Computing (2021–2023), NIT Agartala: 89.5%, 8.95/10, Rank: 6️⃣
  • B.Sc. in Mathematics, Physics, and Computer Science (2017–2020), Banasthali Vidyapith: 85.8%, 8.58/10 🧮
  • Senior Secondary Examination (2016–2017), Board of School Education Haryana: 85.0% 🧑‍🎓
  • Secondary Examination (2014–2015), Board of School Education Haryana: 91.4% 🌟
Experience 🧑‍🔬
  • M.Sc. Thesis (2022–2023) at NIT Agartala: Focused on portfolio optimization under uncertainty 🌐.

Suitability For The Award

Ms. Kanika is an exceptional candidate for the Best Researcher Award, showcasing a strong academic foundation, innovative research contributions, and a deep commitment to advancing applied mathematics, machine learning, and artificial intelligence. Her dedication to leveraging mathematical and computational tools for solving real-world problems highlights her potential to make a significant impact in her field.

Professional Development

Kanika’s professional journey showcases her dedication to research and continuous learning 📚. She has gained expertise in machine learning 🤖, MATLAB 🧪, and scientific computing 🖥️. Her technical skills extend to programming languages like C/C++ and database management systems 💾. As a mathematics enthusiast, she has completed rigorous training programs like the Mathematics Training and Talent Research (MTTS) and the National Mathematics Talent Contest 🏅. She actively participates in workshops and online programs, enhancing her skills in cutting-edge mathematical technologies 🌟. Kanika is also a certified karateka 🥋, showcasing her versatile interests beyond academics.

Research Focus

Ms. Kanika’s research interests lie at the intersection of applied mathematics and emerging technologies 🌐. Her focus areas include optimization 📈, uncertainty theory, numerical analysis, graph theory, machine learning 🤖, and artificial intelligence. She aims to bridge theoretical mathematics with practical computing applications 💻, contributing to fields like computational imaging and decision-making under uncertainty. Currently working on a machine-learning research paper 📝, Kanika aspires to tackle real-life problems 🌍 using her expertise in applied mathematics and AI. Her passion for solving complex problems drives her to explore innovative solutions in these interdisciplinary domains.

Awards and Honors

  • IIT JAM 2021 🎓: All India Rank 2169 (Mathematical Sciences).
  • MTTS Level 1 🏅: Selected in the top 20 students, IISER Thiruvananthapuram (2020).
  • Banaras Hindu University Entrance Exam 🎓: All India Rank 363 (Mathematical Sciences, 2020).
  • Common Entrance Exam (CEE) by NCERT 🏆: State Rank 63 (General), NCERT (2017).
  • National Mathematics Talent Contest 🥇: Top 10%ile, Junior Level Screening Test, AMTI (2014).
  • Certified Karateka 🥋: 8th, 7th, and 6th Kyu (Blue Belt), JKMO (2018).
  • Olympic Value Education Program Ambassador 🏅: Honored by Banasthali Vidyapith (2017).

Publication Top Notes 

  • 📚 Tools and techniques for teaching computer programming: A review – Journal of Educational Technology Systems, 2020, Cited by: 88
  • 🤝 Effect of different grouping arrangements on students’ achievement in collaborative learning – Interactive Learning Environments, 2023, Cited by: 12
  • 🧬 Genetic algorithm‐based approach for making pairs and assigning exercises in programming – Computer Applications in Engineering Education, 2020, Cited by: 8
  • 📖 Enriching WordNet with subject-specific out-of-vocabulary terms using ontology – Data Engineering for Smart Systems, 2022, Cited by: 6
  • 🎓 KELDEC: A recommendation system for extending classroom learning with visual cues – Proceedings of SSIC, 2019, Cited by: 6
  • 🎯 VISTA: A teaching aid to enhance contextual teaching – Computer Applications in Engineering Education, 2021, Cited by: 3
  • 🌐 Linking classroom studies with dynamic environment – International Conference on Computing, Power and Communication, 2019, Cited by: 2
  • 🔄 Effect of varying the size of the initial parent pool in genetic algorithm – International Conference on Contemporary Computing and Informatics, 2014, Cited by: 2
  • 🌍 A review of English to Indian language translator: Anusaaraka – International Conference on Advances in Computer Engineering & Applications, 2014, Cited by: 2

Dr. Tara P Banjade | Artificial Intelligence Awards | Best Researcher Award

Posted on by Global Sensor Awards

Dr. Tara P Banjade | Artificial Intelligence Awards | Best Researcher Award 

Dr. Tara P Banjade, East China University of Technology, Nanchang, China

Dr. Tara P. Banjade is an Associate Professor at the East China University of Technology, Nanchang, China, specializing in applied mathematics, seismic signal processing, and artificial intelligence applications for seismic data processing. He completed his Ph.D. in Applied Mathematics at Harbin Institute of Technology in China in 2020, following a Master’s and Bachelor’s in Mathematics from Tribhuvan University, Nepal. Dr. Banjade’s research focuses on developing mathematical algorithms for denoising seismic data, including 1D earthquake signals and 2D geophysical data like oil, gas, and ground-penetrating radar (GPR) data. His innovative approaches employ techniques such as variational mode decomposition, wavelet transforms, and artificial intelligence, including DARE U-Net for seismic noise attenuation and self-guided singular value decomposition for data edge detection.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award

Dr. Tara P. Banjade demonstrates an impressive academic and research profile, particularly within Applied Mathematics and Seismic Signal Processing, fields which align closely with the scope of the Best Researcher Award. His doctoral education from Harbin Institute of Technology and ongoing research position at East China University of Technology position him as a strong candidate.

Education

  1. Harbin Institute of Technology, Harbin, China
    • Ph.D. in Applied Mathematics
    • Duration: September 2015 – January 2020
  2. Tribhuvan University, Kathmandu, Nepal
    • Master’s in Mathematics
    • Duration: 2012 – 2014
  3. Tribhuvan University, Kathmandu, Nepal
    • Bachelor’s in Mathematics
    • Duration: 2006 – 2010

Work Experience

  1. Associate Professor
    • Institution: East China University of Technology, School of Geophysics and Measurement-Control Technology, Nanchang, Jiangxi, China
    • Duration: March 2023 – Present
  2. Founder/Chairperson
    • Organization: Intellisia Institute for Research and Development, Nepal
  3. Research Director
    • Organization: Girija Prasad Koirala Foundation
    • Duration: 2020 – Present
  4. Visiting Scientist
    • Institution: Research Centre for Applied Science and Technology (RECAST), Tribhuvan University, Nepal
  5. Founding Member and Mathematics Lecturer
    • Institution: Arunima College, Tribhuvan University, Nepal
    • Duration: 2020 – 2023
  6. Executive Member
    • Organization: Nepal Mathematical Society
    • Duration: 2021 – 2024
  7. Visiting Faculty
    • Institution: School of Mathematical Science, Tribhuvan University, Nepa.

Publication top Notes:

Seismic Random Noise Attenuation Using DARE U-Net

Enhancing seismic data by edge-preserving geometrical mode decomposition

Prof. Dr. Tamara Gajic | Artificial Intelligence Awards | Top Researcher Award

Posted on by Global Sensor Awards

Prof. Dr. Tamara Gajic | Artificial Intelligence Awards | Top Researcher Award 

Prof. Dr. Tamara Gajic, Geographical Institute “Jovan Cvijic” Serbian Academy of Sciences and Arts, Belgrade, Serbia

Tamara Gajić is a distinguished Senior Research Associate at the Geographical Institute “Jovan Cvijić” of the Serbian Academy of Sciences and Arts (SASA), specializing in social geography. She holds a Ph.D. in Geosciences from the University of Novi Sad and has extensive experience in research and education across various institutions. Her academic career spans several positions, including Senior Researcher at the Institute of Environmental Engineering, People’s Friendship University of Russia (RUDN University), and Associate Professor at Singidunum University in Belgrade. She has also served as a professor and assistant professor at various universities in Serbia, Bosnia, and Herzegovina. Gajić’s research focuses on rural development, tourism management, and sustainable practices in agritourism, gastrotourism, and sport tourism. She has contributed to numerous projects, including the modernization of tourism study programs in Serbia and feasibility studies for spa tourism. Gajić is an active member of various professional organizations, including the Serbian Geographical Society and the Tourist Organization of Serbia, and has mentored numerous graduate and doctoral students. Her expertise in integrating economics, service quality, and human resources in tourism management has earned her recognition as one of the top 10% of distinguished scientists in Serbia in 2024.

Professional Profile:

SCOPUS

ORCID

GOOGLE SCHOLAR

Suitability of Tamara Gajić for the Top Researcher Award

Tamara Gajić is highly qualified for the Top Researcher Award due to her extensive academic and professional achievements in the fields of Geography, Rural Studies, and Tourism Management. Below are the key reasons why she is a suitable candidate for this prestigious award:

Academic Degrees:

🎓 Ph.D. in Geosciences
📅 2010
University of Novi Sad, Faculty of Sciences, Department of Geography, Tourism and Hotel Management, Serbia 🇷🇸

🎓 M.Sc. in Tourism Management
📅 2007
University of Novi Sad, Faculty of Sciences, Department of Geography, Tourism and Hotel Management, Serbia 🇷🇸

🎓 B.Sc. in Tourism Management
📅 2001
University of Novi Sad, Faculty of Sciences, Department of Geography, Tourism and Hotel Management, Serbia 🇷🇸

Research & Teaching Interests:

🌍 Research Areas:

  • Geography 🌍
  • Rural Studies 🌾
  • Tourism Management 🌐
    Focus on Agrotourism, Gastrotourism, and Sport Tourism 🏞️🍴🏃‍♀️
    Intersection of Economics in Tourism, Service Quality, and Human Resources 💼
    Sustainability in Environment and Tourism 🌱

Previous Employment:

  • Associate Professor
    📅 February 2021 – September 2021
    Faculty of Tourism and Hotel Management, Singidunum University, Belgrade, Serbia 🇷🇸
  • Assistant Professor
    📅 October 2018 – February 2022
    University for Business Studies, Banja Luka, Bosnia and Herzegovina 🇧🇦
  • Professor of Vocational Studies
    📅 October 2008 – February 2021
    Novi Sad Business School, Novi Sad, Serbia 🇷🇸

Publication top Notes:

Innovative Approaches in Hotel Management: Integrating Artificial Intelligence (AI) and the Internet of Things (IoT) to Enhance Operational Efficiency and Sustainability

The Contribution of the Farm to Table Concept to the Sustainable Development of Agritourism Homesteads

Fostering Sustainable Urban Tourism in Predominantly Industrial Small-Sized Cities (SSCs)—Focusing on Two Selected Locations

Leveraging digital platforms for responsible sports tourism: Budapest’s role in the 2020 European football championship

Tourists’ Willingness to Adopt AI in Hospitality—Assumption of Sustainability in Developing Countries

The Adoption of Artificial Intelligence in Serbian Hospitality: A Potential Path to Sustainable Practice